Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/infopibe/everything-claude-code/skill-creategit clone --depth 1 https://github.com/Infopibe/everything-claude-codeWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00006 | $0.00530 |
| Opus 5 | $0.00003 | $0.00265 |
| Sonnet 5 | $0.00001 | $0.00106 |
| Haiku 4.5 | $0.00001 | $0.00053 |
Grade A, and why
skill-create scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to skill-create — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Skill Create Command
Analyze git history to generate Claude Code skills: $ARGUMENTS
Your Task
- Analyze commits - Pattern recognition from history
- Extract patterns - Common practices and conventions
- Generate SKILL.md - Structured skill documentation
- Create instincts - For continuous-learning-v2
Analysis Process
Step 1: Gather Commit Data
# Recent commits
git log --oneline -100
# Commits by file type
git log --name-only --pretty=format: | sort | uniq -c | sort -rn
# Most changed files
git log --pretty=format: --name-only | sort | uniq -c | sort -rn | head -20
Step 2: Identify Patterns
Commit Message Patterns:
- Common prefixes (feat, fix, refactor)
- Naming conventions
- Co-author patterns
Code Patterns:
- File structure conventions
- Import organization
- Error handling approaches
Review Patterns:
- Common review feedback
- Recurring fix types
- Quality gates
Step 3: Generate SKILL.md
# [Skill Name]
## Overview
[What this skill teaches]
## Patterns
### Pattern 1: [Name]
- When to use
- Implementation
- Example
### Pattern 2: [Name]
- When to use
- Implementation
- Example
## Best Practices
1. [Practice 1]
2. [Practice 2]
3. [Practice 3]
## Common Mistakes
1. [Mistake 1] - How to avoid
2. [Mistake 2] - How to avoid
## Examples
### Good Example
```[language]
// Code example
Anti-pattern
// What not to do
### Step 4: Generate Instincts
For continuous-learning-v2:
```json
{
"instincts": [
{
"trigger": "[situation]",
"action": "[response]",
"confidence": 0.8,
"source": "git-history-analysis"
}
]
}
Output
Creates:
skills/[name]/SKILL.md- Skill documentationskills/[name]/instincts.json- Instinct collection
TIP: Run /skill-create --instincts to also generate instincts for continuous learning.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 118 lines · 6 tokens per session scan A 61fa979c3036
skill-create is a command published in the GitHub repository Infopibe/everything-claude-code (8 stars, last pushed 5mo ago), licensed MIT. It adds 6 tokens to every session and 530 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to skill-create, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.